Introduction

Trending YouTube videos capture what is going on in the world through a variety of different categories. YouTube videos are something that almost everyone in the United States is familiar with. However, the types of videos and the logistics behind the videos that make the trending section are not as well known. In this report we will analyze what factors support videos making it into YouTube’s trending section through summaries, tables, and visual representations of our findings from our data set. The data set we will be using to conduct this analysis was created and organized by Rishav Sharma. We pulled the data set on November 14th, 2020 and thus the data we are analyzing contains values from August 3rd, 2020 to November 14th, 2020. It is important to note that our analysis is only for videos in the United States and does not contain correlations between the factors we are analyzing and other countries.

Summary Information

Our dataset has 18798 rows and 16 columns.

The earliest date in our dataset is 2020-08-03 and the latest recorded date is 2020-11-14.

These are the column names: video_id, title, publishedAt, channelId, channelTitle, categoryId, trending_date, tags, view_count, likes, dislikes, comment_count, thumbnail_link, comments_disabled, ratings_disabled, description.

Aggregate Table

For the table, we grouped by categoryId from the dataset to see which category trends the most, and other details that might come with it. We found out that Gaming came out as the most trending category with the highest average views. As for the title stat, we added that to see if having a video title in all caps can influence the ability to trends as shown on the table.

category_names views_mean averagelikes topchannel commentsmean titlestat
Film & Animation 2025344.6 110514.86 David Blaine 9089.492 24.1%
Autos & Vehicles 1109876.9 57941.91 HyundaiWorldwide 4881.367 21.7%
Music 4854943.0 344589.81 Big Hit Labels 47725.599 19.8%
Pets & Animals 950095.6 46729.66 Brave Wilderness 5176.603 34%
Sports 1587992.4 35253.49 Nike 4163.358 23.9%
Travel & Events 487083.7 24737.56 Food Insider 2955.709 26.5%
Gaming 3170215.4 159096.36 The Pixel Kingdom 16318.291 22.9%
People & Blogs 2181098.1 134301.91 Dixie D’Amelio 9798.764 25.8%
Comedy 1365803.7 117477.00 The Tonight Show Starring Jimmy Fallon 9077.497 22.5%
Entertainment 2560955.4 159596.80 MrBeast 13293.515 24.9%
News & Politics 2060328.3 21005.40 Fox News 8310.775 9.9%
How to & Style 1258141.7 73553.66 <U+674E><U+5B50><U+67D2> Liziqi 5947.786 27%
Education 1141692.2 80213.16 Kurzgesagt – In a Nutshell 7600.743 20.1%
Science & Technology 2366718.0 86868.48 Apple 6721.817 18.6%
Nonprofits & Activism 756021.2 35196.44 CORE 4728.560 25.2%

Charts

Average Viewership Per Day

This plot displays the average amount of views trending videos recieved on a given day (Sunday to Saturday). We created this chart to see if there is a relationship between average viewership and the day of the week.

This graph clearly shows that trending videos on Friday receive nearly triple the average viewership. Additionally, Wednesday is a particularly slow day for YouTube videos. This may mean that popular creators should attempt to have a video on the trending page every Friday because this is when they would likely receive the highest viewership.

Boxplot Graph

This graph shows the variation of the time it takes a video to reach the trending page after it’s published. Most of the data is concentrated between the 0 to 5 day range, while there are some outliers above 10 days for most categories. Interestingly enough, the graph also included values with negative values. This is because the published date includes the full date and time, whereas the trending date only includes the month and day. For videos to have a negative value of days it took to reach the trending page, it means that the video was wildly popular enough to be trending on the same date it was uploaded.